physics.flu-dyn

Papers

• Inpainting physics: self-supervised learning for context-driven fluid simulation (2026)
  Jonas Weidner et al.
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• Open Multimodal Datasets and Open-Source Software for Data-Driven Modeling of Multiphase Transport and Thermal Systems (2026)
  Christy Dunlap et al.
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• High-fidelity Modeling of Full-scale Pressurized Water Reactor Flow Fields for Machine Learning Applications (2026)
  Logan A. Burnett et al.
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• Accelerating Bayesian inverse design in computational fluid dynamics using neural operators (2026)
  Bipin Tiwari et al.
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• Deep Learning-based Algebraic Reynolds Stress Closures for RANS Simulations of Turbulent Flows (2026)
  Daniel Dehtyriov et al.
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• Neural Operator-Based Surrogate Model for CFD:Helical Coil Steam Generator in Small Modular Reactor (2026)
  Minseo Lee et al.
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